Linker Optimization in Breast Cancer Multiepitope Peptide Vaccine Design Based on Molecular Study

DOI

10.2991/978-94-6463-062-6_54How to use a DOI?

Keywords

Breast cancer; Linker; Immunoinformatics; Multi-epitope; Vaccine

Abstract

Breast cancer is most common cancer diagnosed in women. The urgency of developing effective therapeutic approaches is needed, both passive and active immunotherapy using vaccines. Immunoinformatics approach for epitope prediction of cancer proteins is one of promising approach in peptide vaccine development. Linker optimization is important parameters in peptide vaccine construction which will affect the conformation, folding and vaccine stability. From our previous study, we generate multiepitope peptide-vaccine consist of seven epitopes: DPVALVAPF, SVAYRLGTL, SQINTLNTL, RFRELVSEF, VTSANIQEF, RPRFRELVS, and MYFEFPQPL. Here we made attempt to optimize the multiepitope structure linked by 5 linker such as AAY, EAAAK, GPGPG, GGGGS, KK using in silico approach. 3D modelling of the multi epitope sequence was conducted via GalaxyTBM. Validation of tertiary structure conducted using Ramachandran plot and quality factor of the structures is being analyzed using ERRAT. Solubility of the designed vaccine was assessed using the Protein Sol webserver. The multi-epitope vaccine physicochemical parameters (pI, hydrophobicity, GRAVY, charges, and molecular weight) were conducted via Peptide Analyzing Tools from Thermofisher Scientific. From the protein validation results and physicochemical features, the best peptide model is model 1 which linked with EAAAK linker. Model 1 can be used as potential multi-epitope agents for breast cancer vaccines.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Fadilah Fadilah
AU  - Rafika Indah Paramita
AU  - Linda Erlina
AU  - Khaerunissa Anbar Istiadi
AU  - Puspita Eka Wuyung
AU  - Aryo Tedjo
PY  - 2022
DA  - 2022/12/22
TI  - Linker Optimization in Breast Cancer Multiepitope Peptide Vaccine Design Based on Molecular Study
BT  - Proceedings of the 4th International Conference on Life Sciences and Biotechnology (ICOLIB 2021)
PB  - Atlantis Press
SP  - 528
EP  - 538
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-062-6_54
DO  - 10.2991/978-94-6463-062-6_54
ID  - Fadilah2022
ER  -